Automated detection and classification of polioviruses from nanopore sequencing reads using piranha

Áine O'Toole*, Rachel Colquhoun, Corey Ansley, Catherine Troman, Daniel Maloney, Zoe Vance, Joyce Akello, Erika Bujaki, Manasi Majumdar, Adnan Khurshid, Yasir Arshad, Muhammad Masroor Alam, Javier Martin, Alexander G Shaw, Nicholas C Grassly, Andrew Rambaut

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Widespread surveillance, rapid detection, and appropriate intervention will be critical for successful eradication of poliovirus. Using deployable next-generation sequencing (NGS) approaches, such as Oxford Nanopore Technologies' MinION, the time from sample to result can be significantly reduced compared to cell culture and Sanger sequencing. We developed piranha (poliovirus investigation resource automating nanopore haplotype analysis), a 'sequencing reads-to-report' solution to aid routine poliovirus testing of both stool and environmental samples and alleviate the bioinformatic bottleneck that often exists for laboratories adopting novel NGS approaches. Piranha can be used for efficient intratypic differentiation of poliovirus serotypes, for classification of Sabin-like polioviruses, and for detection of wild-type and vaccine-derived polioviruses. It produces interactive, distributable reports, as well as summary comma-separated values files and consensus poliovirus FASTA sequences. Piranha optionally provides phylogenetic analysis, with the ability to incorporate a local database, processing from raw sequencing reads to an interactive, annotated phylogeny in a single step. The reports describe each nanopore sequencing run with interpretable plots, enabling researchers to easily detect the presence of poliovirus in samples and quickly disseminate their results. Poliovirus eradication efforts are hindered by the lack of real-time detection and reporting, and piranha can be used to complement direct detection sequencing approaches.

Original languageEnglish
Pages (from-to)veae023
Number of pages12
JournalVirus Evolution
Volume10
Issue number1
Early online date29 Feb 2024
DOIs
Publication statusPublished - Mar 2024

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